Quantum computers can change the financial system. They can solve problems faster and more accurately than the most powerful traditional computers. There are three areas where quantum computers have obvious advantages over traditional computers: simulations, optimization models, and machine learning (ML).
1. Simulation: based on Monte Carlo methods. The use of simulation in the financial industry is everywhere. For example, Monte Carlo methods are used to price financial instruments and manage risks. However, Monte Carlo simulation is computationally intensive and often requires a trade-off between accuracy and efficiency. Quantum computing can perform simulations such as pricing and risk management in almost real-time, without adopting unrealistic assumptions to simplify the model.
2. Optimization models. Financial institutions are performing countless optimization calculations every day such as determining the best investment strategy for the asset portfolio, allocating capital, and managing cash in ATMs. For traditional computers, some optimization problems are difficult, if not impossible, to solve. Quantum computers can perform more precise optimizations in a short period of time without using approximations.
3. Machine learning methods, including neural networks and deep learning. Financial institutions are increasingly using ML. For example, credit scores are used to assess the risk level of loans, and fraudulent behaviors can be detected by discovering patterns that deviate from normal behavior. However, such ML algorithms face the dilemma of dimensionality. The time required to train ML algorithms on traditional computers increases exponentially with the number of dimensions considered. Quantum computers have the potential to surpass traditional algorithms by accelerating ML algorithms (quantum acceleration), enabling them to process more complex analyses and improving accuracy at the same time.
Quantum computing will become a catalyst for scientific discovery and innovation. An important application of quantum computing is particle physics models. These models are usually very complex and require a lot of computational time to perform numerical simulations. Quantum computers will make it possible to accurately model molecular interactions and find the best configuration for chemical reactions. Quantum computers can also improve weather forecasts, optimize transportation routes and supply chains, and help us better understand climate change.
Quantum technology has brought new data transmission, storage and operation methods. Quantum networks can transmit information in the form of entangled qubits between remote quantum processors and can safely use quantum key distribution (QDK) at almost the same time. Until recently, this kind of network could only be operated under laboratory conditions, but it has proven its feasibility in remote secure communication. In addition, data can also be transmitted wirelessly via quantum satellites in space.
Quantum sensing equipment has broad application prospects. According to reports, the device has made progress in quantum radar, imaging, metrology and navigation. For example, through revolutionary improvements in the detection and treatment of diseases, medicine has begun to benefit from quantum sensors.
